Understanding Opportunities and Risks of Synthetic Relationships: Leveraging the Power of Longitudinal Research with Customised AI Tools
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866915061073707008 |
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| author | Ventura, Alfio Köbis, Nils |
| author_facet | Ventura, Alfio Köbis, Nils |
| contents | This position paper discusses the benefits of longitudinal behavioural research with customised AI tools for exploring the opportunities and risks of synthetic relationships. Synthetic relationships are defined as "continuing associations between humans and AI tools that interact with one another wherein the AI tool(s) influence(s) humans' thoughts, feelings, and/or actions." (Starke et al., 2024). These relationships can potentially improve health, education, and the workplace, but they also bring the risk of subtle manipulation and privacy and autonomy concerns. To harness the opportunities of synthetic relationships and mitigate their risks, we outline a methodological approach that complements existing findings. We propose longitudinal research designs with self-assembled AI agents that enable the integration of detailed behavioural and self-reported data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_09086 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding Opportunities and Risks of Synthetic Relationships: Leveraging the Power of Longitudinal Research with Customised AI Tools Ventura, Alfio Köbis, Nils Human-Computer Interaction Artificial Intelligence Computers and Society J.4 This position paper discusses the benefits of longitudinal behavioural research with customised AI tools for exploring the opportunities and risks of synthetic relationships. Synthetic relationships are defined as "continuing associations between humans and AI tools that interact with one another wherein the AI tool(s) influence(s) humans' thoughts, feelings, and/or actions." (Starke et al., 2024). These relationships can potentially improve health, education, and the workplace, but they also bring the risk of subtle manipulation and privacy and autonomy concerns. To harness the opportunities of synthetic relationships and mitigate their risks, we outline a methodological approach that complements existing findings. We propose longitudinal research designs with self-assembled AI agents that enable the integration of detailed behavioural and self-reported data. |
| title | Understanding Opportunities and Risks of Synthetic Relationships: Leveraging the Power of Longitudinal Research with Customised AI Tools |
| topic | Human-Computer Interaction Artificial Intelligence Computers and Society J.4 |
| url | https://arxiv.org/abs/2412.09086 |